Precision Agriculture using Internet of Things and Machine Learning

The agriculture industry is facing a significant challenge due to poor water management, resulting in a considerable decline in crop production. A lot of water used in irrigation is wasted due to inadequate management practices. The inefficient irrigation systems often have poor water flow control, leading to over-extraction of groundwater, which can lead to harming crop yield. To tackle this problem, precision agriculture, which leverages technology to optimize crop production while minimizing waste and environmental harm, has emerged as a viable solution. IoT-based smart irrigation management systems are an integral part of this approach and can play a vital role in achieving water efficiency goals. In this context, an open-source intelligent system that utilizes machine learning-based algorithms and monitors parameters of soil, such as its moisture and temperature, has been developed to predict the irrigation needs of a field. By forecasting the amount of water required by crops, this system can ensure that the water is utilized more efficiently. The results of the system, which has been successfully deployed on a demo scale, are very promising. The smart system has the potential to revolutionize the way irrigation is managed and help address the water efficiency challenges facing the agriculture industry.